• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.3
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• pp.193-201
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• 2002

For measuring a traffic symbolic confusion Quantity and symbolic air pleasantness, we use fuzzy sensor algorithm maded by symbolic information Quantity. Hut for implementation of fuzzy sensor, we use some symbolic information item, this method cannot produce precise output because we use vague fuzzy rule method and we cannot abundance fuzzy for precision of fuzzy rule method. For this reason, this paper introduce new fuzzy sensor algorithm composed of not fuzzy rule method but using Analytic Hierachy Process. To prove that new method is good, two type of fuzzy sensor applied to traffic signal controller and through much passing vehicle, two fuzzy sensor compared each other.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.457-459
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• 2003

This paper considers the application of Fuzzy Logic to Smart Decision process of Smart Sensor system that interprets and response to the change of environmental parameters. The considered system consists of three sensors: temperature sensor, humidity sensor and pressure sensor. The smartness of system is constituted by the applying of Fuzzy Logic. The paper discusses the technical details of the application of Fuzzy Logic for making the system to be smarter.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.103-109
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• 2001

Soft sensor is an effective method to deal with the estimation of variables, which are difficult to measure because of the reasons of economy or technology. Fuzzy logic system can be used to develop the soft sensor model by infinite rules, but the fuzzy dividing of variable sets is a key problem to achieve an accurate fuzzy logic model, In this paper, we proposed a new method to develop soft sensor model based on fuzzy neural network. First, using a novel method to divide the variable fuzzy sets by the process input and output data. Second, developing the fuzzy logic model based on that fuzzy set dividing. After that, expressing the fuzzy system with a fuzzy neural network and getting the initial soft sensor model based FNN. Last, adjusting the relative parameters of soft sensor model by the BP learning method. The effectiveness of the method proposed and the preferable generalization ability of soft sensor model built are demonstrated by the simulation.

• Nuclear Engineering and Technology
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• v.33 no.5
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• pp.483-497
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• 2001

In this work, a neuro-fuzzy inference system combined with the wavelet denoising, PCA (principal component analysis) and SPRT (sequential probability ratio test) methods is developed to detect the relevant sensor failure using other sensor signals. The wavelet denoising technique is applied to remove noise components in input signals into the neuro-fuzzy system The PCA is used to reduce the dimension of an input space without losing a significant amount of information. The PCA makes easy the selection of the input signals into the neuro-fuzzy system. Also, a lower dimensional input space usually reduces the time necessary to train a neuro-fuzzy system. The parameters of the neuro-fuzzy inference system which estimates the relevant sensor signal are optimized by a genetic algorithm and a least-squares algorithm. The residuals between the estimated signals and the measured signals are used to detect whether the sensors are failed or not. The SPRT is used in this failure detection algorithm. The proposed sensor-monitoring algorithm was verified through applications to the pressurizer water level and the hot-leg flowrate sensors in pressurized water reactors.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.780-785
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• 1992

We present a multi-sensor fusion method in positioning control of a robot by using fuzzy logic. In general, the vision sensor is used in the gross motion control and the force/torque sensor is used in the fine motion control. We construct a fuzzy logic controller to combine the vision sensor data and the force/torque sensor data. Also, we apply the fuzzy logic controller to the peg-in-hole process. Simulation results uphold the theoretical results.

• Proceedings of the Korean Nuclear Society Conference
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• 1998.05a
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• pp.321-328
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• 1998

A controller and sensor fault tolerant system jot a steam generator is designed with fuzzy logic. A structure of the : proposed fault tolerant redundant system is composed of a supervisor and two fuzzy weighting modulators. A supervisor alternatively checks a controlled and a sensor induced performances to identify Which Part, a controller or a sensor, is faulty. In order to analyze controller induced performance both an error and a charge in error of the system output an chosen as fuzzy variables. The fuzzy logic jot a sensor induced performance uses two variables : a deviation between two sensor outputs and its frequency, Fuzzy weighting modulator generates an output signal compensated for faulty input signal. Simulations show that the : proposed fault tolerant control scheme jot a steam generator regulates welt water level by suppressing fault effect of either controllers or sensors. Therefore through duplicating sensors and controllers with the proposed fault tolerant scheme, both a reliability of a steam generator control and sensor system and that of a power plant increase even mote.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.472-475
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• 2005

In this paper, we propose a Kalman-fuzzy control method using multi-sensor. The proposed method is to obtain a robust sensor data and to integrate multi-sensor data using fuzzy system. in order to verify the effectiveness of the proposed method, we performed the simulation for the position of an elertro hydraulic actuator. The results showed a good performance.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.448-451
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• 2005

For measuring a traffic symbolic confusion quantity and symbolic air pleasantness, we use fuzzy sensor algorithm maded by symbolic information quantity. But for implementation of fuzzy sensor, we use some symbolic information item, this method cannot produce precise output because we use vague fuzzy rule method and we cannot abundance fuzzy for precision of fuzzy rule method. For this reason this paper introduce new fuzzy sensor algorithm composed of not fuzzy rule method but using Analytic Hierachy Process. To prove that new method is good, two type of fuzzy sensor applied to traffic signal controller and through much passing vehicle, two fuzzy sensor compared each other.

• Journal of information and communication convergence engineering
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• v.1 no.4
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• pp.174-176
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• 2003

This paper considers the application of Fuzzy Logic to Smart Decision process of Smart Sensor system that interprets and response to the change of environmental parameters. The considered system consists of three sensors: temperature sensor, humidity sensor and pressure sensor. The smartness of system is constituted by the applying of Fuzzy Logic. The paper discusses the technical details of the application of Fuzzy Logic for making the system to be smarter.

• Proceedings of the Korea Society for Simulation Conference
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• 2005.05a
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• pp.5-9
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• 2005

One of the imminent problems to be solved within wireless sensor network is to balance out energy dissipation among deployed sensor nodes. In this paper, we present a transmission relay method of communications between BS (Base Station) and CHs (Cluster Heads) for balancing the energy consumption and extending the average lifetime of sensor nodes by the fuzzy logic application. The proposed method is designed based on LEACH protocol. The area deployed by sensor nodes is divided into two groups based on distance from BS to the nodes. RCH (Relay Cluster Head) relays transmissions from CH to BS if the CH is in the area far away from BS in order to reduce the energy consumption. RCH decides whether to relay the transmissions based on the threshold distance value that is obtained as a output of fuzzy logic system. Our simulation result shows that the application of fuzzy logic Provides the better balancing of energy depletion and Prolonged lifetime of the nodes.